Remove Sequence.generate_random_poisson and update Sequence.generate_random_exponential
#108
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…exponential to correctly process lambda parameter, and update Sequence.generate_random_exponential to include a reference to Poisson point processes and Poisson distributions
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Please also take a good look at whether the new docs are readable, thanks! |
…ndom_exponential fix
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Resolves #78.
Poisson distributions are not continuous distributions, and they have a non-zero probability for the integer 0. As such, they are an invalid way of sampling random IOIs for a sequence. As such, this PR removes the
Sequence.generate_random_poissonclass method.The random sequences relevant in the context of a Poisson process/distribution were already generated by
Sequence.generate_random_exponential. That docstring is also updated so that users can still find relevant information regarding "Poisson" in the documentation.However, the
lamparameter was passed incorrectly to NumPy'sexponentialrandom function. Thescaleparameter of that function equals the inverse of the typicallambdaparametrization of the exponential distribution and Poisson distribution. I.e., lambda corresponds to the rate/frequency, scale corresponds to the mean interval duration.This PR also fixes that, but brings up the question which parametrization we want to provide? The "maths one" or the "NumPy one"? Alternatively, we could also provide 2 optional parameters (
lamandscale), explicitly check that users provide exactly one, and correctly pass either one to NumPy. @Jellevanderwerff, thoughts?